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updates for release
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‎.bumpversion.toml‎

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[[tool.bumpversion.files]]
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filename = "./src/sbmlsim/__init__.py"
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filename = "./_docs/_quarto.yml"

‎RELEASE.md‎

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* update release notes in `release-notes` with commit
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* make sure all tests run (`tox -p`)
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* check formating and linting (`ruff check`)
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* build documentation
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* build documentation (`cd _docs | quartodoc build | quatro render`)
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* test bump version (`uvx bump-my-version bump [major|minor|patch] --dry-run -vv`)
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* bump version (`uvx bump-my-version bump [major|minor|patch]`)
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* `git push --tags` (triggers release)

‎_docs/api/sensitivity.classification.qmd‎

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| [sensitivity_classification](#sbmlsim.sensitivity.classification.sensitivity_classification) | Classification of local sensitivity as per WHO IPCS guidance. |
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| [sensitivity_classification_symbol](#sbmlsim.sensitivity.classification.sensitivity_classification_symbol) | Calculates symbol for sensitivity classification. |
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| [uncertainty_classification](#sbmlsim.sensitivity.classification.uncertainty_classification) | Classification of uncertainty as per WHO IPCS guidance. |
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| [uncertainty_classification_symbol](#sbmlsim.sensitivity.classification.uncertainty_classification_symbol) | Calculates symbol for uncertainty classification. |
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### sensitivity_classification { #sbmlsim.sensitivity.classification.sensitivity_classification }
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International Programme on Chemical Safety (IPCS). Characterization and application of physiologically based pharmacokinetic models in risk assessment.
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World Health Organization; 2010. Contract No.: 9.
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### uncertainty_classification_symbol { #sbmlsim.sensitivity.classification.uncertainty_classification_symbol }
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```python
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sensitivity.classification.uncertainty_classification_symbol(u)
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```
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Calculates symbol for uncertainty classification.

‎_docs/api/sensitivity.sensitivity_sampling.qmd‎

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- minimum and maximum
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- lower and upper quantiles (5% and 95%)
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Uncertainty is calculated as Ui,j = (Percentile97.5(i,j) - Percentile2.5(i,j)) / Percentile50(i,j)
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This approach focuses on uncertainty propagation rather than variance-based
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sensitivity indices and is therefore complementary to local and Sobol-based
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methods.

‎_docs/objects.json‎

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‎docs/api/sensitivity.classification.html‎

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<li class="sidebar-item">
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<div class="sidebar-item-container">
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<a href="../api/sensitivity.html" class="sidebar-item-text sidebar-link">
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<span class="menu-text">Sensitivity</span></a>
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<span class="menu-text">Sensitivity &amp; Uncertainty</span></a>
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</div>
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</li>
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<li class="sidebar-item">
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<li><a href="#sbmlsim.sensitivity.classification.sensitivity_classification" id="toc-sbmlsim.sensitivity.classification.sensitivity_classification" class="nav-link" data-scroll-target="#sbmlsim.sensitivity.classification.sensitivity_classification">sensitivity_classification</a></li>
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<li><a href="#sbmlsim.sensitivity.classification.sensitivity_classification_symbol" id="toc-sbmlsim.sensitivity.classification.sensitivity_classification_symbol" class="nav-link" data-scroll-target="#sbmlsim.sensitivity.classification.sensitivity_classification_symbol">sensitivity_classification_symbol</a></li>
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<li><a href="#sbmlsim.sensitivity.classification.uncertainty_classification" id="toc-sbmlsim.sensitivity.classification.uncertainty_classification" class="nav-link" data-scroll-target="#sbmlsim.sensitivity.classification.uncertainty_classification">uncertainty_classification</a></li>
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<li><a href="#sbmlsim.sensitivity.classification.uncertainty_classification_symbol" id="toc-sbmlsim.sensitivity.classification.uncertainty_classification_symbol" class="nav-link" data-scroll-target="#sbmlsim.sensitivity.classification.uncertainty_classification_symbol">uncertainty_classification_symbol</a></li>
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<td><a href="#sbmlsim.sensitivity.classification.uncertainty_classification">uncertainty_classification</a></td>
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<td>Classification of uncertainty as per WHO IPCS guidance.</td>
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</tr>
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<tr class="even">
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<td><a href="#sbmlsim.sensitivity.classification.uncertainty_classification_symbol">uncertainty_classification_symbol</a></td>
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<td>Calculates symbol for uncertainty classification.</td>
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</tr>
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<section id="sbmlsim.sensitivity.classification.sensitivity_classification" class="level3">
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<section id="references-1" class="level4 doc-section doc-section-references">
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<h4 class="doc-section doc-section-references anchored" data-anchor-id="references-1">References</h4>
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<p>International Programme on Chemical Safety (IPCS). Characterization and application of physiologically based pharmacokinetic models in risk assessment. World Health Organization; 2010. Contract No.: 9.</p>
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</section>
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</section>
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<section id="sbmlsim.sensitivity.classification.uncertainty_classification_symbol" class="level3">
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<h3 class="anchored" data-anchor-id="sbmlsim.sensitivity.classification.uncertainty_classification_symbol">uncertainty_classification_symbol</h3>
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<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>sensitivity.classification.uncertainty_classification_symbol(u)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
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<p>Calculates symbol for uncertainty classification.</p>
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</section>
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</section>
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</main> <!-- /main -->
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<script id="quarto-html-after-body" type="application/javascript">

‎docs/api/sensitivity.sensitivity_fast.html‎

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<nav class="page-navigation">
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<a href="../api/sensitivity.html" class="pagination-link" aria-label="Sensitivity">
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<i class="bi bi-arrow-left-short"></i> <span class="nav-page-text">Sensitivity</span>
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<a href="../api/sensitivity.html" class="pagination-link" aria-label="Sensitivity &amp; Uncertainty">
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<i class="bi bi-arrow-left-short"></i> <span class="nav-page-text">Sensitivity &amp; Uncertainty</span>
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<div class="nav-page nav-page-next">

‎docs/api/sensitivity.sensitivity_local.html‎

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‎docs/api/sensitivity.sensitivity_morris.html‎

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‎docs/api/sensitivity.sensitivity_sampling.html‎

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<p>Uncertainty is calculated as Ui,j = (Percentile97.5(i,j) - Percentile2.5(i,j)) / Percentile50(i,j)</p>
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<p>This approach focuses on uncertainty propagation rather than variance-based sensitivity indices and is therefore complementary to local and Sobol-based methods.</p>
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<section id="classes" class="level2">
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<h2 class="anchored" data-anchor-id="classes">Classes</h2>

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